code: def test_replace_scoring(
      estimator, fit_kwargs, scoring, xy_classification, mocker
  ):
      X, y = xy_classification
      inc = Incremental(
          estimator(max_iter=1000, random_state=0, tol=1e-3)
      )
      inc.fit(X, y, **fit_kwargs)
  
      patch = mocker.patch.object(dask_ml.wrappers, "get_scorer")
  
      inc.score(X, y)
  
      assert patch.call_count == 1
      patch.assert_called_with(scoring, compute=True)
  
imports: import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  import sklearn.datasets
  import sklearn.model_selection
  from dask.array.utils import assert_eq
  from scipy.sparse import csr_matrix
  from sklearn.base import clone
  from sklearn.linear_model import SGDClassifier, SGDRegressor
  from sklearn.pipeline import make_pipeline
  import dask_ml.feature_extraction.text
  import dask_ml.metrics
  from dask_ml.metrics.scorer import check_scoring
  from dask_ml.wrappers import Incremental
label_desc: Use image node_id 10 for calling a global function with example usage: test_replace_scoring(estimator, fit_kwargs, scoring, xy_classification, mocker) without return types